Challenges and opportunities for efficient computing with FAWN

This paper presents the architecture and motivation for a clusterbased, many-core computing architecture for energy-efficient, dataintensive computing. FAWN, a Fast Array of Wimpy Nodes, consists of a large number of slower but efficient nodes coupled with low-power storage. We present the computing...

Full description

Saved in:
Bibliographic Details
Published in:Operating systems review 2011-02, Vol.45 (1), p.34-44
Main Authors: Vasudevan, Vijay, Andersen, David G., Kaminsky, Michael, Franklin, Jason, Kozuch, Michael A., Moraru, Iulian, Pillai, Padmanabhan, Tan, Lawrence
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents the architecture and motivation for a clusterbased, many-core computing architecture for energy-efficient, dataintensive computing. FAWN, a Fast Array of Wimpy Nodes, consists of a large number of slower but efficient nodes coupled with low-power storage. We present the computing trends that motivate a FAWN-like approach, for CPU, memory, and storage. We follow with a set of microbenchmarks to explore under what workloads these FAWN nodes perform well (or perform poorly), and briefly examine scenarios in which both code and algorithms may need to be re-designed or optimized to perform well on an efficient platform. We conclude with an outline of the longer-term implications of FAWN that lead us to select a tightly integrated stacked chip and-memory architecture for future FAWN development.
ISSN:0163-5980
DOI:10.1145/1945023.1945029